// TODO(b/173073199): Use shape. Enable tests in unified_api_test.cc once
  // resolved.
  Type type;
  TF_RETURN_IF_ERROR(ConvertDataTypeToTensor(dtype, builder_, &type));
  *handle =
      new MlirTensor(func_.getBody().front().addArgument(type, func_.getLoc()));
  return absl::OkStatus();
}

Status MlirAbstractOp::AddInput(AbstractTensorHandle* input) {
  if (current_ods_input_ >= op_def_->input_arg_size())

  // Move all regions from the old `mhlo.while` op to its replacement.
  new_while.getCond().takeBody(region_while.getCond());
  new_while.getBody().takeBody(region_while.getBody());

  // Forward result from old `mhlo.while` with replacement.
  SmallVector<Value> old_while_results = region_while.getResults();
  SmallVector<Value> new_while_results = new_while.getResults();

          next_values_to_visit.push_back(
              while_op.getCond().front().getArgument(operand_number));
          next_values_to_visit.push_back(
              while_op.getBody().front().getArgument(operand_number));
          continue;
        }

        if (llvm::isa<mlir::TF::IdentityOp, mlir::TF::CastOp,
                      mlir::TF::ReadVariableOp>(owner)) {

                              ArrayRef<Type> dataset_types) {
  const Location loc = reduce_dataset.getLoc();
  auto while_input_types = dataset_while.getOperandTypes();
  auto& body_region = dataset_while.getBody();
  Block* body_block = builder.createBlock(&body_region);
  auto body_arguments = body_block->addArguments(
      while_input_types, SmallVector<Location>(while_input_types.size(), loc));

// the function body.
std::optional<llvm::StringMap<FunctionMetadata>> GetFunctionMetadatas(
    func::FuncOp func_op) {
  llvm::StringMap<FunctionMetadata> metadatas;
  WalkResult result = func_op.getBody().walk([&](Operation *op) {
    std::string op_host = GetHost(op);
    FunctionMetadata &func_metadata = metadatas[op_host];
    func_metadata.original_name = func_op.getName();

  void runOnOperation() override;
};

// TODO(fengliuai): migrate to use modify_io_nodes pass.
void RemoveQuantizationAdaptorOps(func::FuncOp func) {
  mlir::OpBuilder builder(func.getBody());
  auto& bb = func.front();
  auto loc = func.getLoc();

  int num_args = bb.getNumArguments();
  llvm::SmallVector<Type, 4> input_types;
  input_types.reserve(num_args);

    assertThat(response.status).isEqualTo("HTTP/1.1 202 That'll do pig")
  }

  @Test
  fun setBodyAdjustsHeaders() {
    val response = MockResponse().setBody("ABC")
    assertThat(headersToList(response)).containsExactly("Content-Length: 3")
    assertThat(response.getBody()!!.readUtf8()).isEqualTo("ABC")
  }

  @Test
  fun mockResponseAddHeader() {
    val response =
      MockResponse()
        .clearHeaders()

      (*buffer_to_size)[region.getArgument(i)] = {size_arg,
                                                  it->getSecond().fixed};
    }
  };

  // Rewrite body.
  Region& body_region = while_op.getBody();
  modify_region_arguments(body_region);
  if (failed(DecomposeTensorListOpsInternal(
          &body_region.front(), module, buffer_to_size,
          decomposed_partitioned_call_callees))) {
    return failure();

      llvm::ArrayRef<std::pair<mlir::ValueRange, mlir::Type>>{},
      mlir::ValueRange{}, mlir::TypeRange{});
  builder.setInsertionPoint(&replicate.getBody().front(),
                            replicate.getBody().front().begin());

  llvm::SmallVector<mlir::Type, 8> result_types;
  auto cluster = builder.create<mlir::tf_device::ClusterOp>(
      mlir::UnknownLoc::get(&context), result_types);

                              const bool legacy_float_scale = false,
                              const bool is_qdq_conversion = false)
      : fn_(func_op),
        builder_(func_op.getBody()),
        is_signed_(is_signed),
        bit_width_(bit_width),
        disable_per_channel_(disable_per_channel),
        op_quant_spec_getter_(op_quant_spec_getter),